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A practical guide to robust optimization
Robust optimization is a young and active research field that has been mainly developed in the last 15 years. Robust optimization is very useful for practice, since it is tailored to the information at hand, and it leads ...
A survey of adjustable robust optimization
Static robust optimization (RO) is a methodology to solve mathematical optimization problems with uncertain data. The objective of static RO is to find solutions that are immune to all perturbations of the data in a so-called ...
Load dependent lead time modelling: a robust optimization approach
Although production planning models using nonlinear CFs have shown promising results for semiconductor wafer fabrication facilities, the lack of an effective methodology for estimating the CFs is a significant obstacle to ...
Decision rule bounds for two-stage stochastic bilevel programs
(Society for Industrial and Applied Mathematics Publications, 2018)
We study two-stage stochastic bilevel programs where the leader chooses a binary here-and-now decision and the follower responds with a continuous wait-and-see decision. Using modern decision rule approximations, we construct ...
Robust dual response optimization
(Taylor & Francis, 2016)
This article presents a robust optimization reformulation of the dual response problem developed in response surface methodology. The dual response approach fits separate models for the mean and the variance, and analyzes ...
A robust optimization approach for production planning under exogenous planned lead times
Many production planning models applied in semiconductor manufacturing represent lead times as fixed exogenous parameters. However, in reality, lead times must be treated as realizations of released lots' cycle times, which ...
A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty
We focus on rapid needs assessment operations conducted immediately after a disaster to identify the urgent needs of the affected community groups, and address the problem of selecting the sites to be visited by the ...
The value of quality grading in remanufacturing under quality level uncertainty
(Taylor & Francis, 2020)
In remanufacturing, variability in quality levels of available cores (end-of-life products) has an impact on both the process cost and the process time. While previous research suggests that quality grading adds value, ...
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